# Performance Profiler

> Systematic performance profiling for Node.js, Python, and Go applications. Identifies CPU, memory, and I/O bottlenecks, generates flamegraphs, analyzes bundle sizes, optimizes database queries, runs load tests with k6 and Artillery. Always measures before and after. Use when investigating a slow endpoint, planning a performance budget, or hunting a memory leak in production.

- Skill: `thedixitjain/performance-profiler` (Agent Skill, multi-file: 4 files)
- Install (CLI): `npx skillmds add thedixitjain/performance-profiler`
- Raw SKILL.md: https://api.skillmd.com/api/skills/thedixitjain/performance-profiler/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Finance & Business
- Author: thedixitjain (https://skillmd.com/u/thedixitjain)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/thedixitjain/performance-profiler

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# Performance Profiler

**Tier:** POWERFUL  
**Category:** Engineering  
**Domain:** Performance Engineering  

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## Overview

Systematic performance profiling for Node.js, Python, and Go applications. Identifies CPU, memory, and I/O bottlenecks; generates flamegraphs; analyzes bundle sizes; optimizes database queries; detects memory leaks; and runs load tests with k6 and Artillery. Always measures before and after.

## Core Capabilities

- **CPU profiling** — flamegraphs for Node.js, py-spy for Python, pprof for Go
- **Memory profiling** — heap snapshots, leak detection, GC pressure
- **Bundle analysis** — webpack-bundle-analyzer, Next.js bundle analyzer
- **Database optimization** — EXPLAIN ANALYZE, slow query log, N+1 detection
- **Load testing** — k6 scripts, Artillery scenarios, ramp-up patterns
- **Before/after measurement** — establish baseline, profile, optimize, verify

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## When to Use

- App is slow and you don't know where the bottleneck is
- P99 latency exceeds SLA before a release
- Memory usage grows over time (suspected leak)
- Bundle size increased after adding dependencies
- Preparing for a traffic spike (load test before launch)
- Database queries taking >100ms

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## Quick Start

```bash
# Analyze a project for performance risk indicators
python3 scripts/performance_profiler.py /path/to/project

# JSON output for CI integration
python3 scripts/performance_profiler.py /path/to/project --json

# Custom large-file threshold
python3 scripts/performance_profiler.py /path/to/project --large-file-threshold-kb 256
```

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## Golden Rule: Measure First

```bash
# Establish baseline BEFORE any optimization
# Record: P50, P95, P99 latency | RPS | error rate | memory usage

# Wrong: "I think the N+1 query is slow, let me fix it"
# Right: Profile → confirm bottleneck → fix → measure again → verify improvement
```

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## Node.js Profiling
→ See references/profiling-recipes.md for details

## References

- [references/profiling-recipes.md](references/profiling-recipes.md) — Node.js/Python/Go profiling commands, flamegraph generation, heap snapshots
- [references/optimization-playbook.md](references/optimization-playbook.md) — before/after measurement template, quick-win optimization checklist (DB/Node/bundle/API), common pitfalls, best practices

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**Source:** [`alirezarezvani/claude-skills`](https://github.com/alirezarezvani/claude-skills) → `engineering/skills/performance-profiler/SKILL.md`